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A Comparative Phylogenetic Study of Genetics and Folk Music

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A Comparative Phylogenetic Study of Genetics and Folk Music Mol Genet Genomics DOI 10.1007/s00438-012-0683-y ORIGINAL PAPER A comparative phylogenetic study of genetics and folk music Horolma Pamjav • Zolta´n Juha´sz • Andrea Zala´n • Endre Ne´meth • Bayarlkhagva Damdin Received: 7 December 2011 / Accepted: 21 February 2012 Ó Springer-Verlag 2012 Abstract Computer-aided comparison of folk music corresponding musical cultures were also compared using from different nations is one of the newest research areas. an automatic overlap analysis of parallel melody styles for We were intrigued to have identified some important 31 Eurasian nations. We found that close musical relations similarities between phylogenetic studies and modern folk of populations indicate close genetic distances (\0.05) with music. First of all, both of them use similar concepts and a probability of 82%. It was observed that there is a sig- representation tools such as multidimensional scaling for nificant correlation between population genetics and folk modelling relationship between populations. This gave us music; maternal lineages have a more important role in the idea to investigate whether these connections are folk music traditions than paternal lineages. Furthermore, merely accidental or if they mirror population migrations the combination of these disciplines establishing a new from the past. We raised the question; does the complex interdisciplinary research field of ‘‘music-genetics’’ can be structure of musical connections display a clear picture and an efficient tool to get a more comprehensive picture on the can this system be interpreted by the genetic analysis? This complex behaviour of populations in prehistoric time. study is the first to systematically investigate the incidental genetic background of the folk music context between Keywords Y haplogroups Á mtDNA haplogroups Á Folk different populations. Paternal (42 populations) and music Á Music genetics Á Human demographic history maternal lineages (56 populations) were compared based on Fst genetic distances of the Y chromosomal and mtDNA haplogroup frequencies. To test this hypothesis, the Introduction Computer-aided comparison of traditional music features Communicated by S. Hohmann. from different cultures is one of the newest research areas. Electronic supplementary material The online version of this While a considerable amount of genetic studies has been article (doi:10.1007/s00438-012-0683-y) contains supplementary carried out in connection with human evolution history and material, which is available to authorized users. migrations, relations between genetic research and music cultures have never been investigated. Thus, we turned our H. Pamjav (&) Á A. Zala´n Á E. Ne´meth DNA Laboratory, Institute of Forensic Medicine, attention to correlation patterns between genetic data and Network of Forensic Science Institutes, Budapest, folk music melodies. PO Box 216, 1536, Hungary Human history is tightly related with a history of pop- e-mail: [email protected] ulation migration. Patterns of genetic diversity provide Z. Juha´sz information about population history because each major Department of Complex Systems, Research Institute for demographic event left an imprint on genomic diversity of Technical Physics and Materials Science, Budapest, Hungary populations. These demographic signatures are passed from generation to generation, thus the genomes of modern B. Damdin Department of Molecular Biology, Faculty of Biology, National individuals reflect their demographic history. Studies for University of Mongolia, Ulaanbaatar, Mongolia evolutionary history have benefited from analyses of 123 Mol Genet Genomics mitochondrial DNA (mtDNA) and the non-recombining variation is an essential feature of most oral cultures. Cross- region of the Y chromosome. Because these regions of cultural analysis of different nations in Eurasia drew a well- human genome are not shuffled by recombination, they are interpretable network of ‘‘genetic’’ relations between transmitted intact from one generation to the next, reveal- musical traditions (Juha´sz 2000; Juha´sz and Sipos 2009). ing the maternal and paternal lineages of a population. This led us to the question whether these connections are Populations share mtDNA or Y chromosome lineages as a merely accidental or can they possibly relate to the result of common origins or gene flow (admixture). Use of migration of populations in any way? Does the complex mtDNA and the Y chromosome has been extensively structure of musical connections display a clear picture and studied and used in migration studies and in the analysis of can we interpret this connection system on a genetic basis population history and origins (Wells et al. 2001; Cinnioglu as well? et al. 2004; Nasidze et al. 2005; Pakendorf et al. 2006). Y chromosome markers tend to show restricted regional distribution, or population specificity, making them ideal in Materials and methods marking unique migration events (Hammer et al. 1997). Similarly, the variation of mtDNA between different pop- Materials ulation groups can be used to estimate the time back to common ancestors. In the last few years, there has been In the present work, we describe the results of a computer- significant progress in reconstructing the detailed genea- aided cross-cultural analysis of 31 representative Eurasian logical branching order of the tree topologies for both and North-American folksong collections, and a parallel mtDNA and the non-recombining region of the Y chro- study of genetic relations between the corresponding pop- mosome (Jobling and Tyler-Smith 2003; Underhill and ulation groups. Our melody database contains digital Kivisild 2007; Karafet et al. 2008). notations of 31 cultures, each of them consisting of Affinities between populations may result from their 1,000–2,500 melodies. The studied cultures are as follows: common origin or from recent admixture due to geographic Chinese, Mongolian, Kyrgyz, Volga Region (Mari–Chuv- proximity. In particular, genetic distances between popu- ash–Tatar–Votiac), Sicilian, Bulgarian, Azeri, Anatolian, lations can generally be related to geographic distances, Karachay, Hungarian, Slovakian, Moravian, Romanian, according to a model of isolation by distance (Cavalli- Finnish, Norwegian, German, Luxembourgish, French, Sforza and Bodmer 1977). But this is not relevant in all Dutch, Irish–Scottish–English (one group), Spanish, cases. Dakota, Komi, Khanty, Croatian–Serbian (Balkan group), According to earlier reports, correlation between genetic Kurdish, Russian from the Pskov Area, Navajo and three distance and language as a cultural marker has been regions of Poland: Great Poland, Warmia and Cassubia. debated (Nettle and Harriss 2003). We, however, set out to Simultaneously with the musical database investigation, examine relationships between genetic distance and folk we also calculated corresponding genetic distance matrices music cultures. using widely used software tools (Schneider et al. 2000) The comparative study of different folk music cultures from published data for those populations compared above, goes back to the early 20th century. Barto´k and Koda´ly with the following differences: (1) no genetic data were identified certain musical styles of Hungarian folk music found for the Luxembourgish, Karachay and Dakota Indi- being common with Mari, Chuvash, as well as Anatolian ans, (2) Y chromosomal and mtDNA genetic data were melodies (Barto´k 1949; Koda´ly 1971). These results initi- used for the Croatian; Tatar, Mari, Udmurt/Votiac and ated the expansion of a digitized international folksong Chuvash (instead of Volga Region); Irish and Scottish database (the European Folksong Catalogue), and a soft- populations separately, (3) genetic data of three Hungarian ware system for mathematical analysis of the data in the speaking groups (Hungarian, Szekler and Csango) were 1960s (Cse´bfalvy et al. 1965). Although this project, orga- used (Szekler and Csango Y chromosomal data is unpub- nized by the Hungarian Academy of Sciences was inter- lished). The Szeklers and Csangos are Hungarian speaking rupted, development of computation tools led to the later ethnic groups living in Romania, (4) one Polish population resurrection of the idea (Toiviainen 1996, 2000; Leman data were used for the Y and mtDNA genetic comparisons; 2000; Toiviainen and Eerola 2002; Kranenburg et al. 2009; whereas three Polish folksong databases arising from dif- Garbens et al. 2007; Huron 1996; Juha´sz (2009). ferent areas of Poland were analysed. In recent years, we have developed and enhanced a software system which characterizes the overall similarity Methods for genetic analysis of different folk song databases using a scalar measure. The basic idea of this system is that musical information prop- We calculated genetic distances (Fst) with AMOVA based agates and evolves by endless variation of melodies, since on Y chromosomal and mtDNA haplogroup frequencies 123 Mol Genet Genomics with Arlequin 2.0 software (Schneider et al. 2000). Mul- contour vectors of D dimensions (D element pitch tidimensional scaling (MDS) plots were constructed with sequences) from the digital codes of music notations ViSta 7.9.2.4 software. (Juha´sz 2006). Since D was the same for each melody, the Y chromosomal haplogroups were combined into groups contours could be compared to each other using a common C, D, E, F, I, J2, K, L, N1c, PxR1a and R1a, so that Euclidean distance function defined in the same published sources could be used for comparisons (Bosch D-dimensional melody space, irrespective
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